Implementation Of Quantification Research Articles

Interdisciplinary Implementation of Quantification of Blood Loss During Vaginal and Cesarean Delivery [23C

Interdisciplinary Implementation of Quantification of Blood Loss During Vaginal and Cesarean Delivery [23C

Efficient implementation of generalized quantification in relational query languages

We present research aimed at improving our understanding of the use and implementation of quantification in relational query languages in general and SQL in particular. In order to make our results as general as possible, we use the framework of Generalized Quantification. Generalized Quantifiers (GQs) are high-level, declarative logical operators that in the past have been studied from a theoretical perspective. In this paper we focus on their practical use, showing how to incorporate a dynamic set of GQs in relational query languages, how to implement them efficiently and use them in the context of SQL. We present experimental evidence of the performance of the approach, showing that it improves over traditional (relational) approaches.

Quantification of shallow water quality parameters by means of remote sensing

Quantification of quality parameters of inland and near shore waters by means of remote sensing has encountered varying degrees of success in spite of the high variability of the parameters under consideration and limitations of remote sensors themselves. This paper comprehensively evaluates the quantification of four types of water quality parameters: inorganic sediment particles, phytoplankton pigments, coloured dissolved organic material and Secchi disk depth. It concentrates on quantification requirements, as well as the options in selecting the most appropriate sensor data for the purpose. Relevant factors, such as quantification implementation and validation of the quantified results are also extensively discussed. This review reveals that the relationship between in situ samples and their corresponding remotely sensed data can be linear or nonlinear, but are nearly always site-specific. The quantification has been attempted from terrestrial satellite data largely for suspended sediments and chlorophyll concentrations. The quantification has been implemented through integration of remotely sensed imagery data, in situ water samples and ancillary data in a geographic information system (GIS). The introduction of GIS makes the quantification feasible for more variables at an increasingly higher accuracy. Affected by the number and quality of in situ samples, accuracy of quantification has been reported in different ways and varies widely.